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Comparing the Robustness of Trading Systems to Higher-Order Uncertainty

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  • Hyun Song Shin

Abstract

This paper compares the performance of a decentralized market with that of a dealership market when traders have differential information. Trade occurs as a result of equilibrium actions in a Bayesian game, where uncertainty is captured by a finite state space and information is represented by partitions on this space. In the benchmark case of trade with common knowledge of endowments, the two mechanisms deliver virtually identical outcomes. However, with differential information, the dealership market has strictly higher trading volume, and yields an efficient post-trade allocation in most states. In contrast, the decentralized market suffers from suboptimal trading volume. The reason for this poor performance is the vulnerability of the decentralized market to higher-order uncertainty concerning the fundamentals of the market. Traders may know that mutually beneficial trade is feasible, and perhaps know that they know, and yet a failure of common knowledge that this is so precludes efficient trade. The dealership market is robust to this type of uncertainty.

Suggested Citation

  • Hyun Song Shin, 1996. "Comparing the Robustness of Trading Systems to Higher-Order Uncertainty," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 63(1), pages 39-59.
    • Handle: RePEc:oup:restud:v:63:y:1996:i:1:p:39-59.
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    File URL: http://hdl.handle.net/10.2307/2298114
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    Cited by:

    1. Antonio Cabrales & Rosemarie Nagel & Roc Armenter, 2007. "Equilibrium selection through incomplete information in coordination games: an experimental study," Experimental Economics, Springer;Economic Science Association, vol. 10(3), pages 221-234, September.
    2. Chwe, Michael Suk-Young, 1999. "The Reeded Edge and the Phillips Curve: Money Neutrality, Common Knowledge, and Subjective Beliefs," Journal of Economic Theory, Elsevier, vol. 87(1), pages 49-71, July.
    3. Kuksov, Dmitri, 2006. "Search, common knowledge, and competition," Journal of Economic Theory, Elsevier, vol. 130(1), pages 95-108, September.
    4. Füss, Roland & Grabellus, Markus & Mager, Ferdinand & Stein, Michael, 2018. "Something in the air: Information density, news surprises, and price jumps," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 53(C), pages 50-75.
    5. Germano, Fabrizio, 2003. "Bertrand-edgeworth equilibria in finite exchange economies," Journal of Mathematical Economics, Elsevier, vol. 39(5-6), pages 677-692, July.
    6. Stephen Morris & Hyun Song Shin, "undated". "Approximate Common Knowledge and Co-ordination: Recent Lessons from Game Theory," Penn CARESS Working Papers 72042421d029130510780dde2, Penn Economics Department.
    7. Stephen Morris & Hyun Song Shin, 2000. "Global Games: Theory and Applications," Cowles Foundation Discussion Papers 1275R, Cowles Foundation for Research in Economics, Yale University, revised Aug 2001.
    8. Frédéric KOESSLER, 2002. "Strategic Knowledge Sharing in Bayesian Games: Applications," Working Papers of BETA 2002-02, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    9. Timothy Shields & Baohua Xin, 2012. "Higher-order Beliefs in Simple Trading Models," Working Papers 12-18, Chapman University, Economic Science Institute.
    10. Isabel Schnabel & Hyun Song Shin, 2018. "Money and trust: lessons from the 1620s for money in the digital age," BIS Working Papers 698, Bank for International Settlements.
    11. Lunawat, Radhika, 2021. "Learning from trading activity in laboratory security markets with higher-order uncertainty," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 90(C).

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